List the digit sum mod 7 of the first 10 primes larger than 53. This starts with 0 0 6 1. What do you have to do to generate the next number? Count the numbers

List the digit sum mod 7 of the first 10 primes larger than 53. This starts with 0 0 6 1. What do you have to do to generate the next number? Count the numbers in the output to figure out that you have done 4 numbers, add 1 because the 5th prime after 53 is next, figure out that this prime is 73, calculate the digit sum 10 and then find the remainder 3. There is just no way that a neural network has learned to do this. But ask for this as a table with prime, digit sum and digit sum mod 7 and it becomes trivial. First prime after 53? Output 59. Digit sum? Output 14. Mod 7? Output 0. Next prime after 59? Output 61. Digit sum? Output 7. Mod 7? Output 0. Next prime after 61? Output 67. Digit sum? Output... This is what chain of thought does, it allows the neural network to only do simple tasks it knows how to do, output the result and continue from there with the next step. You would keep those intermediate results in your short-term memory but a large language model has none and so the best thing it can do is to dump them into the output and read them back when generating the next token. The proposed pause token has essentially the same goal, the neural network can dump some state into the output to work on it but this output is not considered part of the response. It is essentially an attempt to hide the chain of thought process and only respond with the final answer. The hard part will of course be to train the neural network to make efficient use of this, to actually output useful intermediate results before the pause is over and the response gets extracted.